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DOE OSTI2026

Pion and kaon PDFs from lattice QCD via large momentum effective theory and short-distance factorization

In this paper, we present a first-principles lattice-QCD calculation of the unpolarized quark PDF for the pion and the kaon. The lattice data rely on matrix elements calculated for boosted mesons coupled to non-local operators containing a Wilson line. The calculations on this lattice ensemble correspond to two degenerate light, a strange, and a charm quark (𝑁 𝑓 = 2 + 1 + 1), using maximally twisted mass fermions with a clover term. The lattice volume is 32 3 × 64, with a lattice spacing of 0.0934 fm, and a pion mass of 260 MeV. Matrix elements are calculated for hadron boosts of |𝑃 3 | = 0, 0.41, 0.83, 1.25, 1.66, and 2.07 GeV. To match lattice QCD results to their light-cone counterparts, we employ two complementary frameworks: the large-momentum effective theory (LaMET) and the short-distance factorization (SDF). Using these approaches in parallel, we also test the lattice data to identify methodology-driven systematics. Results are presented for the standard quark PDFs, as well as the valence sector. Beyond obtaining the PDFs, we also explore the possibility of extracting information on SU(3) flavor-symmetry-breaking effects. For LaMET, we also parametrize the momentum dependence to obtain the infinite-momentum PDFs. Since the present calculation is performed on a single ensemble at a pion mass of 260 MeV and fixed lattice spacing, the uncertainties reported are statistical only, and systematic uncertainties remain to be addressed in future multi-ensemble studies.

Miller, Joshua [Temple University, Philadelphia, P↗

DOE OSTI2024

Hybrid Modeling of Three-Phase Grid-Supporting Inverters for Dynamic Studies

Grid technologies connected by power electronic converter (PEC) interfaces continually implement grid support functions mandated by grid codes and standards. The transition to converter-based generation demands precise PEC models to assess system dynamics, which have been previously overlooked in conventional power systems. This study proposes a hybrid method for analyzing grid-connected three-phase PEC dynamics with the IEEE standard 1547-2018 Volt-VAr mode that combines physics and data-driven techniques. The physics model reflects the PEC’s internal behavior, whereas the data-driven modeling technique evaluates the grid-supporting capabilities of the smart PEC. The system identification approach is used to generate dynamic PEC models based on changing grid voltage and measured current injected into the grid by the PEC. In the Volt-VAr support mode, a detailed topological model including switches is utilized to compare the goodness-of-fit of the extracted hybrid dynamic model. The results demonstrate that the hybrid PEC model in the Volt-VAr mode accurately matches the dynamics with the topological model.

Subedi, Sunil↗

DOE OSTI2026

Hybrid Dynamic Modeling of Smart Inverter

This letter proposes a novel hybrid method for assessing grid-connected three-phase converter interfaced resources (CIR) dynamics with the IEEE standard 1547-2018 grid support functions (GSFs), which blends physics and data-driven techniques. First, the letter derives an analytical model of a CIR to represent the internal physics and data-driven model (DDM) using a system identification algorithm to represent the rest of the dynamics, including the GSF. The derived hybrid model combines the analytical model of CIR and DDM, which balances accuracy and flexibility and is compared with the detailed switched model. Furthermore, the efficacy of the proposed approach to represent the advanced CIR dynamics is substantiated by power hardware-in-the-loop experiment data where real measurements from a commercial CIR are used to cross-validate the proposed approach. Furthermore, the results indicate that despite simple, the hybrid model accurately reproduces the dynamics of the detailed CIR model with an acceptable accuracy.

Data-driven model↗

DOE OSTI2022

A Simplified Numerical Approach to Characterize the Thermal Response of a Moving Bed Solar Reactor

Abstract Concentrated solar thermochemical storage in the form of a zero-emission fuel is a promising option to produce long-duration energy storage. Solar fuel is produced using a cavity reactor that captures concentrated solar radiation from a solar field of heliostats. In this paper, heat transfer model of a tubular plug-flow reactor designed and manufactured for a solar fuel production is presented. Experimental data collected from a fixed bed tubular reactor testing are used for model comparison. The system consists of an externally heated tube with counter-current flowing gas and moving solid particles as the heated media. The proposed model simulates the dynamic behavior of temperature profiles of the tube wall, gas, and particles under various gas flowrates and residence times. The heat transfer between gas–wall, solid particle–wall, and gas–solid particle is numerically studied. The model results are compared with the results of experiments done using a 4 kW furnace with a 150 mm heating zone surrounding a horizontal alumina tube (reactor) with 50.8 mm outer diameter and thickness of 3.175 mm. Solid fixed particles of magnesium manganese oxide (MgMn2O4) with the size of 1 mm are packed within the length of 250 mm at the center of the tube length. Simulation results are assessed with respect to fixed bed experimental data for four different gas flowrates, namely, 5, 10, 15, and 20 standard liters per minute of air, and furnace temperatures in the range of 200–1200 °C. The simulation results showed good agreement with maximum steady state error that is less than 6% of those obtained from the experiments for all runs. The proposed model can be implemented as a low-order physical model for the control of temperature inside plug-flow reactors for thermochemical energy storage applications.

Engineering↗

DOE OSTI2022

Factorization of Binary Matrices: Rank Relations, Uniqueness and Model Selection of Boolean Decomposition

The application of binary matrices are numerous. Representing a matrix as a mixture of a small collection of latent vectors via low-rank decomposition is often seen as an advantageous method to interpret and analyze data. In this work, we examine the factorizations of binary matrices using standard arithmetic (real and nonnegative) and logical operations (Boolean and $\mathbb{Z}$ 2 ). We examine the relationships between the different ranks, and discuss when factorization is unique. In particular, we characterize when a Boolean factorization X = W$\land$H has a unique W, a unique H (for a fixed W), and when both W and H are unique, given a rank constraint. We introduce a method for robust Boolean model selection, called BMFk, and show on numerical examples that BMFk not only accurately determines the correct number of Boolean latent features but reconstruct the pre-determined factors accurately.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

METABOLIC: high-throughput profiling of microbial genomes for functional traits, metabolism, biogeochemistry, and community-scale functional networks

Background Advances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent; however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and microbial contributions to biogeochemical cycling. Results We present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry studies using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the microbiome, potential microbial metabolic handoffs and metabolite exchange, reconstruction of functional networks, and determination of microbial contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, community-scale microbial functional networks using a newly defined metric “MW-score” (metabolic weight score), and metabolic Sankey diagrams. METABOLIC takes ~ 3 h with 40 CPU threads to process ~ 100 genomes and corresponding metagenomic reads within which the most compute-demanding part of hmmsearch takes ~ 45 min, while it takes ~ 5 h to complete hmmsearch for ~ 3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut. Conclusion METABOLIC enables the consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available under GPLv3 at https://github.com/AnantharamanLab/METABOLIC.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

AmeriFlux FLUXNET-1F US-GLE GLEES

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-GLE GLEES. This is the FLUXNET version of the carbon flux data for the site US-GLE GLEES produced by applying the standard ONEFlux (1F) software. Site Description - The Glacier Lakes Ecosystem Experiments Site (GLEES) site is located on land owned by the U.S. government and managed by US Forest Service as part of the Medicine Bow National Forest. Many of the trees in the immediate vicinity of the site are older than 400 years, inter-dispersed among trees much younger in age. This widespread age distribution is most likely a derivation of one of two scenarios: 1) A widespread stand replacement about 400 years ago followed by a slow replacement; 2) Intermittent random disturbances over the past 400 years (Bradford et al. 2008). A decade long spruce beetle outbreak that peaked in 2008 resulted in the mortality of 85% of the forested basal area. There are a few private land holdings in the area, with scattered uncorked mining claims. Following the establishment of the National Forest, mining was banned and grazing was closed in the early 1990's in the upper portion of the GLEES site. Recreation in the winter, when snow can remain in patches into the summer months, snow mobiling and cross country skiing are popular. During the limited summer, hiking, camping and fishing are common activities. The site is accessible by vehicle only during the summer on Forest Road FDR 317, and in the winter, the tower is only reachable via snowmobile.

Frank, John↗

DOE OSTI2025

AmeriFlux FLUXNET-1F US-Sta Saratoga

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Sta Saratoga. This is the FLUXNET version of the carbon flux data for the site US-Sta Saratoga produced by applying the standard ONEFlux (1F) software. Site Description - Sagebrush steppe ecosystem

Ewers, Brent [University of Wyoming]↗

DOE OSTI2026

AmeriFlux FLUXNET-1F US-Cwt Coweeta

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Cwt Coweeta. This is the FLUXNET version of the carbon flux data for the site US-Cwt Coweeta produced by applying the standard ONEFlux (1F) software. Site Description - Mature, secondary, deciduous-dominated forest. Located in southern Appalachian mountains, cove location, near base of forested catchment. Proximity close to USFS Coweeta Hydrologic Laboratory offices. Forest harvesting until early 1930s, unmanaged since.

Oishi, A. Christopher [USDA Forest Service]↗

DOE OSTI2026

AmeriFlux FLUXNET-1F CA-LU2 Lutose

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CA-LU2 Lutose. This is the FLUXNET version of the carbon flux data for the site CA-LU2 Lutose produced by applying the standard ONEFlux (1F) software. Site Description - Lutose is a peat plateau that burned from a moderate forest fire in June 2007. Prior to the fire the site was likley an open canopy of stunted black spruce and a ground layer of Labrador tea shurbs and lichen or sphagnum. No black spruce survived the fire and lichens were still completely absent during this study. By 2019, most charred tree boles has fallen over and vegetation recovery was dominated by dense Labrador tea shrubs and sparse regenerating black spruce with around >150cm of peat.

Schulze, Christopher [University of Alberta]↗

DOE OSTI2026

AmeriFlux FLUXNET-1F BR-Xpw XomanoFlux

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site BR-Xpw XomanoFlux. This is the FLUXNET version of the carbon flux data for the site BR-Xpw XomanoFlux produced by applying the standard ONEFlux (1F) software. Site Description - The site is located in the northern Pantanal, in central South America. The site is a grazing area used for cattle ranching and is subject to seasonal flooding during rainy seasons (November to April). Dry seasons are typically May to October.

Dalmagro, Higo [Universidade de Cuiabá - UNIC]↗

DOE OSTI2021

Learning crystal field parameters using convolutional neural networks

We present a deep machine learning algorithm to extract crystal field (CF) Stevens parameters from thermodynamic data of rare-earth magnetic materials. The algorithm employs a two-dimensional convolutional neural network (CNN) that is trained on magnetization, magnetic susceptibility and specific heat data that is calculated theoretically within the single-ion approximation and further processed using a standard wavelet transformation. We apply the method to crystal fields of cubic, hexagonal and tetragonal symmetry and for both integer and half-integer total angular momentum values J J of the ground state multiplet. We evaluate its performance on both theoretically generated synthetic and previously published experimental data on CeAgSb _2 2 , PrAgSb _2 2 and PrMg _2 2 Cu _9 9 , and find that it can reliably and accurately extract the CF parameters for all site symmetries and values of J J considered. This demonstrates that CNNs provide an unbiased approach to extracting CF parameters that avoids tedious multi-parameter fitting procedures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Characterization of U Isotope Ratios by Laser Ablation MC-ICP-MS for IAEA Safeguards

This project will develop methodology to identify and analyze U and Pu containing particles using laser ablation MC-ICP-MS. The proposed work will involve: i) setup and optimization of the LA-MC-ICP-MS system, ii) testing and validation by analysis of QC standards, iii) designing analytical protocols for single particles, and iv) developing a data processing system. Ultimately, this project will output a detailed operating procedure documenting the experimental techniques and data processing routines required to perform particle identification and analysis by laser ablation MC-ICP-MS, that can be shared with IAEANWAL laboratories.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Development of Analytical Method for Measuring U and Pu Particles by Laser Ablation MC-ICP-MS for the NWAL

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2019

TARDIS. I. A Constrained Reconstruction Approach to Modeling the z ~ 2.5 Cosmic Web Probed by Lyα Forest Tomography

Recent Lyα forest tomography measurements of the intergalactic medium (IGM) have revealed a wealth of cosmic structures at high redshift (z ~ 2.5). In this work, we present the Tomographic Absorption Reconstruction and Density Inference Scheme (TARDIS), a new chronocosmographic analysis tool for understanding the formation and evolution of these observed structures. Here, we use maximum likelihood techniques with a fast nonlinear gravitational model to reconstruct the initial density field of the observed regions. We find that TARDIS allows accurate reconstruction of smaller-scale structures than standard Wiener-filtering techniques. Applying this technique to mock Lyα forest data sets that simulate ongoing and future surveys such as CLAMATO, Subaru PFS, or the ELTs, we are able to infer the underlying matter density field at observed redshift and classify the cosmic web structures. We find good agreement with the underlying truth in both the characteristic eigenvalues and eigenvectors of the pseudo-deformation tensor, with the eigenvalues inferred from 30 m class telescopes correlated at r = 0.95 relative to the truth. As an output of this method, we are able to further evolve the inferred structures to late time (z = 0) and also track the trajectories of coeval z = 2.5 galaxies to their z = 0 cosmic web environments.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

County Level Annual Population Projections for SSP3 and SSP5

This dataset consist of annual (2020-2100) county-level population projections for the United States (U.S.) for Shared Socioeconomic Pathways (SSPs) 3 and 5. The original decadal state-level data is used as an input to the gridded population data model to downscale the state-level projections for each SSP to a 1 km grid. The 1 km data is then aggregated to the county-level using the 2020 TIGER/Line county shapefiles from the U.S. Census Bureau. The two data files are shared as .csv files with the following structure: Rows = Data for individual counties which are identified using their Federal Information Processing Standard (FIPS) code. The FIPS code is stored in the first column. Columns = Each year from 2020-2100 is an individual column. For easier reference, the state name associated with each row is stored in the last column. Values in each cell are the downscaled estimated population for that county-year combination. Values are fractional due to the weighting scheme used in the downscaling. The paper and model source code cited in the "Related Works" section describes the initial source of the population projections.

FIPS↗

DOE OSTI2021

Why Plan for Utility-Scale Solar?

The Solar@Scale project is a DOE Solar Energy Technologies Office-funded collaboration between the American Planning Association and International City/County Management Association (ICMA) to provide best practices and guidance for local communities in planning for large-scale PV development. As a member of the Solar@Scale advisory committee, I have been asked to present on trends and land use projections for large-scale solar to demonstrate why local governments will likely see growing demand for solar energy development. These slides represent an introduction to projections from NREL's Standard Scenarios, Cambium, LBNL's Utility-Scale Solar report, and other data sources on the level of solar energy development that can be expected across the country.

48 EE - Weatherization and Intergovernmental Progr↗

DOE OSTI2023

Unbalanced Nested Random Effects Estimation of Variance Components

To investigate the contributing factors of variance in the measurement of an iodine 127 (127I) sample, we implement a nested random effects analysis of variance (ANOVA). Historically, the reported uncertainty on a measurement of 127I has been obtained by methods of forward uncertainty propagation because there is typically only one replicate of a given sample for which to estimate the uncertainty. When samples are processed there are several types of quality control (QC) standards analyzed along-side the unknown samples with two to five replicates for each. Assuming the variance observed in these replicate QC standards is representative of that of the unknown samples, we use these data in a nested random effects ANOVA to estimate the total uncertainty of a measurement. We demonstrate this approach with two sets of measurements from Idaho National Laboratory and compare the results with the forward uncertainty propagation approach. Variance component estimates for the coarsest level of the nesting structure were most imprecise because replicates were most limited at these levels. We find that the results largely agree between forward propagation and ANOVA, and the greatest contributors of variance are due to instrument variation and chemical processing, with human processing being among the smallest contributors. This analysis provides reassurance that the reported uncertainties using forward propagation are reasonable and the process is well controlled. We propose a future designed experiment to increase replicates at the coarsest level of the hierarchy to improve estimates of these variance components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗